START_DATE = "2022-06-15" # start date for historical data
RSI_TIME_WINDOW = 7 #number of days


import requests
import pandas as pd 
import datetime as dt
import plotly.express as px
import matplotlib.pyplot as plt
import plotly.graph_objects as go
#import pandas_datareader.data as web
from plotly.subplots import make_subplots
import warnings
warnings.filterwarnings('ignore')

## URLS and names
urls = ["https://www.cryptodatadownload.com/cdd/Bitfinex_EOSUSD_d.csv", 
        "https://www.cryptodatadownload.com/cdd/Bitfinex_EDOUSD_d.csv",
        "https://www.cryptodatadownload.com/cdd/Bitfinex_BTCUSD_d.csv",
        "https://www.cryptodatadownload.com/cdd/Bitfinex_ETHUSD_d.csv",
        "https://www.cryptodatadownload.com/cdd/Bitfinex_LTCUSD_d.csv",
       ]

crypto_names = ["EOS Coin (EOS)",
                "Eidoo (EDO)",
                "Bitcoin (BTC)",
                "Ethereum (ETH)",
                "Litecoin (LTC)"
               ]

## Data download and loading 
def df_loader(urls , start_date = "2021-01-01"):
    filenames = []
    all_df = pd.DataFrame()
    for idx,url in enumerate(urls):
        req = requests.get(url,verify=False)
        url_content = req.content
        filename = url[48:]
        csv_file = open( filename , 'wb')
        csv_file.write(url_content)
        csv_file.close()
        filename = filename[:-9]
        filenames.append(filename)
    for file in filenames:
        df = pd.read_csv(file + "USD_d.csv", header = 1, parse_dates=["date"])
        df = df [df["date"] > start_date]
        df.index = df.date
        df.drop(labels = [df.columns[0],df.columns[1],df.columns[8]] , axis = 1 , inplace = True)
        all_df = pd.concat([all_df,df], ignore_index=False)

    return all_df , filenames

def computeRSI (data, time_window):
    diff = data.diff(1).dropna()
    up_chg = 0 * diff
    down_chg = 0 * diff
    up_chg[diff > 0] = diff[ diff>0 ]
    down_chg[diff < 0] = diff[ diff < 0 ]
    up_chg_avg = up_chg.ewm(com=time_window-1, min_periods=time_window).mean()
    down_chg_avg = down_chg.ewm(com=time_window-1, min_periods=time_window).mean()
    rs = abs(up_chg_avg/down_chg_avg)
    rsi = 100 - 100/(1+rs)
    return rsi

all_df , filenames = df_loader(urls , start_date=START_DATE)

crypto_df = []
for file in filenames:
    symbol = file + str("/USD")
    temp_df = pd.DataFrame(all_df[all_df["symbol"] == symbol])
    temp_df.drop(columns= ["symbol"] ,inplace = True)
    temp_df["close_rsi"] = computeRSI(temp_df['close'], time_window=RSI_TIME_WINDOW)
    temp_df["high_rsi"] = 30
    temp_df["low_rsi"] = 70
    exec('%s = temp_df.copy()' % file.lower())
    crypto_df.append(temp_df)

## plot 
fig = make_subplots(rows=3, 
                    cols=2,
                    shared_xaxes=True,
                    specs=[[{"rowspan": 2}, {"rowspan": 2}], [{"rowspan": 1}, {"rowspan": 1}] , [{},{}]]
                    
                   )
date_buttons = [
{'step': "all", 'label': "All time"},
{'count':  1, 'step': "year", 'stepmode': "backward", 'label': "Last Year"},
{'count':  1, 'step': "year", 'stepmode': "todate", 'label': "Current Year"},
{'count':  1, 'step': "month", 'stepmode': "backward", 'label': "Last 2 Months"},
{'count':  1, 'step': "month", 'stepmode': "todate", 'label': "Current Month"},
{'count':  7, 'step': "day", 'stepmode': "todate", 'label': "Current Week"},
{'count':  4, 'step': "day", 'stepmode': "backward", 'label': "Last 4 days"},
{'count':  1, 'step': "day", 'stepmode': "backward", 'label': "Today"},
               ]
buttons = []
i = 0
j=0
COUNT = 8
vis = [False] * len(crypto_names) * COUNT
for df in crypto_df:
    for k in range(COUNT):
        vis[j+k] = True
    buttons.append({ 'label' : crypto_names[i],
                     'method' : 'update',
                     'args'   : [{'visible' : vis},
                                {'title'  : crypto_names[i] + ' Charts and Indicators'}
                                ] }
                  )
    i+=1
    j+=COUNT
    vis = [False] * len(crypto_names)* COUNT
for df in crypto_df:
    fig.add_trace(
        go.Candlestick(x= df.index,
                       open  = df['open'],
                       high  = df['high'],
                       low   = df['low'],
                       close = df['close'],
                       showlegend =False
                                ),
                  row=1, 
                  col=1)
    fig.add_trace(
        go.Bar(x =df.index ,
               y=df["Volume USD"],
               showlegend =False, 
               marker_color='aqua'),
        row=3, 
        col=1)
    fig.add_trace(
        go.Scatter(x=df.index, y=df['close'],
                   mode='lines',
                  showlegend =False,
                   line=dict(color="red", width=4)),
        row=1, 
        col=2)
    fig.add_trace(
        go.Scatter(x=df.index,
                   y=df['low'],
                   fill='tonexty',
                   mode='lines',
                   showlegend =False,                   
                   line=dict(width=2, color='pink', dash='dash')),
        row=1, 
        col=2)
    fig.add_trace(
        go.Scatter(x=df.index, 
                   y=df['high'],
                   fill='tonexty',
                   mode='lines',
                   showlegend =False, 
                   line=dict(width=2, color='pink', dash='dash')),
        row=1, 
        col=2)
    fig.add_trace(
        go.Scatter(x=df.index, y=df['close_rsi'],
                   mode='lines',
                  showlegend =False,
                   line=dict(color="aquamarine", width=4)),
        row=3, 
        col=2)
    fig.add_trace(
        go.Scatter(x=df.index,
                   y=df['low_rsi'],
                   fill='tonexty', 
                   mode='lines',
                   showlegend =False,                   
                   line=dict(width=2, color='aqua', dash='dash')),
        row=3, 
        col=2)
    fig.add_trace(
        go.Scatter(x=df.index, 
                   y=df['high_rsi'],
                   fill='tonexty',
                   mode='lines',
                   showlegend =False, 
                   line=dict(width=2, color='aqua', dash='dash')),
        row=3, 
        col=2)

fig.update_xaxes(
        tickfont = dict(size=15, family = 'monospace', color='#B8B8B8'),
        tickmode = 'array',
        ticklen = 6,
        showline = False,
        showgrid = True,
        gridcolor = '#595959',
        ticks = 'outside')
fig.update_layout(
    spikedistance=100, 
    xaxis_rangeslider_visible=False,
    hoverdistance=1000)
fig.update_xaxes(
    showspikes=True,  
    spikesnap="cursor",
    spikemode="across"
                )
fig.update_yaxes(
    showspikes=True, 
    spikesnap='cursor',
    spikemode="across"                 
                )
fig.update_yaxes(
        tickfont = dict(size=15, family = 'monospace', color='#B8B8B8'),
        tickmode = 'array',
        showline = False,
        ticksuffix = '$',
        showgrid = True,
        gridcolor = '#595959',
        ticks = 'outside')
fig.update_layout(
                  width=1120,
                  height=650,
                  font_family   = 'monospace',
                  xaxis         = dict(rangeselector = dict(buttons = date_buttons)),
                  updatemenus   = [dict(type = 'dropdown',
                                        x = 1.0,
                                        y = 1.108,
                                        showactive = True,
                                        active = 2,
                                        buttons = buttons)],
                  title         = dict(text = '<b>Cryptocurrencies  Dashboard<b>',
                                       font = dict(color = '#FFFFFF' ,size = 22), 
                                       x = 0.50),
                  font          = dict(color="blue"), 
                  annotations   = [
                                  dict( text = "<b>Choose Cryptocurrency: <b>",
                                        font = dict(size = 20 , color = "#ffffff"),
                                        showarrow=False,
                                        x = 1.02, 
                                        y = 1.20,
                                        xref = 'paper', yref = "paper",
                                        align = "left"),
                                  dict( text = "<b>Candlestick Chart <b>",
                                        font = dict(size = 20,  color = "#ffffff"),
                                        showarrow=False,
                                        x = 0.12, 
                                        y = 0.285,
                                        xref = 'paper', yref = "paper",
                                        align = "left"),
                                  dict( text = "<b>Price Chart<b>",
                                        font = dict(size = 20,  color = "#ffffff"),
                                        showarrow=False,
                                        x = 0.82, 
                                        y = 0.285,
                                        xref = 'paper', yref = "paper",
                                        align = "left"),
                                  dict( text = "<b>Volume Traded<b>",
                                        font = dict(size = 20,  color = "#ffffff"),
                                        showarrow=False,
                                        x = 0.14, 
                                        y = -0.53,
                                        xref = 'paper', yref = "paper",
                                        align = "left"),
                                  dict( text = "<b>Relative Strength Index (RSI)<b>",
                                        font = dict(size = 20,  color = "#ffffff"),
                                        showarrow=False,
                                        x = 0.94, 
                                        y = -0.53,
                                        xref = 'paper', yref = "paper",
                                        align = "left")
                  ],
                template= "plotly_dark"
                )    
for i in range(0,5*COUNT):
    fig.data[i].visible = False
for i in range(COUNT):
    fig.data[i].visible = True
fig.layout["xaxis"]["rangeslider"]["visible"] = False
fig.layout["xaxis2"]["rangeslider"]["visible"] = False
fig.layout["xaxis5"]["rangeslider"]["visible"] = True
fig.layout["xaxis6"]["rangeslider"]["visible"] = True
fig.layout["xaxis5"]["rangeslider"]["borderwidth"] = 4
fig.layout["xaxis6"]["rangeslider"]["borderwidth"] = 4
fig.layout["xaxis5"]["rangeslider"]["bordercolor"] = "aqua"
fig.layout["xaxis6"]["rangeslider"]["bordercolor"] = "aqua"
fig.layout["yaxis6"]["ticksuffix"] = ""
fig.layout["yaxis6"]["range"] = [10,100]
fig.show()

%%javascript
IPython.notebook.save_notebook()

import os
os.system('jupyter nbconvert --to html CryptoDashboard.ipynb')